基于图像分析的自动化码头集装箱边缘检测与定位问题研究

Research on Edge Detection and Location of Automated Terminal Container Based on Image Analysis

集装箱边缘检测与定位是自动化集装箱码头岸边与堆场装卸作业过程中的一个关键决策内容,在环境(气候、照明等)多变的情况下,其检测与定位过程具有不确定性、动态性、复杂性、随机性等特点。面向自动化集装箱码头,探索通过边缘特征提取、聚类分析、霍夫变换等技术对拍摄的图像进行处理,研究在当前环境下有效过滤光点、噪声等其他不利因素的影响,得到集装箱的轮廓和位置信息,便于机械吊具进行对箱和吊箱工作。研究成果能够有效利用现有资源,提高集装箱边缘直线和角点识别的准确度、图像识别的效率和质量,实现科学有序的自动化和智能化作业,提高装卸作业效率和设备利用率,降低能源消耗,从而提升港口生产作业水平及其核心竞争力。

As a key decision-making content in the process of automated container terminal shore and yard loading and unloading operations,container edge detection and location are characterized by uncertainty,dynamics,complexity and randomness,especially in the case of changeable environment(climate,lighting,etc.).This paper is for automated container terminals,through the edge feature extraction,clustering analysis,Hough transform and other technologies for image processing,the influence of other unfavorable factors such as effective filtering of light spot,noise under the current environment is studied,and the contour and location information of containers are obtained,which facilitate for mechanical spreader to work on boxes and lifting boxes.The research results,effectively utilize existing resources,can improve the accuracy of line and corner identification of container edges,and the efficiency and quality of image recognition.Therefore,the scientific and orderly automation and intelligent operation are realized,the efficiency of loading and unloading operations and equipment utilization can be improved,and energy consumption can be reduced.Thus the level of port production operations and its core competitiveness can be improved.